Investigations on Rating Computer Sciences Conferences

Abstract

The rating of Computer Science (CS) conferences are important as it influences how papers published at the conferences and may also be used to evaluate research. In this paper, we proposed a method, rsIT, based on a small given set of top conference (pivots) and a relatedness measure based this set as well as basic baseline methods using citation count and field rating. We experimented with a snapshot dataset from Microsoft Academic Graph together with conference data from Microsoft Academic Search. We evaluated the conference ratings from our methods with the CCF conference rating list. We showed that rsIT correlates well with CCF rating and correlates better than ratings from using a baseline ranking with citation count or field rating.

The coverage of Microsoft Academic: analyzing the publication output of a university

“…Harzing (2016) identified only six journal articles related to Microsoft Academic Search and bibliometrics. In contrast, MA has already spurred great interest in a short period of time and triggered several studies that focus on bibliometric topics, such as four studies on visualization and mapping (De Domenico, Omodei, & Arenas, 2016;Portenoy, Hullman, & West, 2016;Portenoy, & West, 2017, Tan et al, 2016. Furthermore, there are eleven studies that deal with the development of indicators and algorithms (Effendy & Yap, 2016;Effendy & Yap, 2017;Herrmannova & Knoth, 2016b;Luo, Gong, Hu, Duan, & Ma, 2016;Medo & Cimini, 2016;Ribas, Ueda, Santos, Ribeiro-Neto, & Ziviani, 2016;Sandulescu & Chiru, 2016;Wesley-Smith, Bergstrom, & West, 2016;Vaccario, Medo, Wider, & Mariani, 2017;Wilson, Mohan, Arif, Chaudhury, & Lall, 2016;Xiao et al, 2016). Finally, there are four studies that assess the potential of MA for evaluative bibliometrics.…”